Abstract

Homeostatic processes are believed to contribute to the stability of neuronal networks that are perpetually influenced by Hebbian forms of synaptic plasticity. Whereas the rules governing the targeting and trafficking of AMPA and NMDA subtypes of glutamate receptors during rapid Hebbian LTP have been extensively studied, those that are operant during homeostatic forms of synaptic strengthening are less well understood. Here, we used biochemical, biophysical, and pharmacological approaches to investigate glutamate receptor regulation during homeostatic synaptic plasticity. We show in rat organotypic hippocampal slices that prolonged network silencing induced a robust surface upregulation of GluA2-lacking AMPARs, not only at synapses, but also at extrasynaptic dendritic and somatic regions of CA1 pyramidal neurons. We also detected a shift in NMDAR subunit composition that, in contrast to the cell-wide surface delivery of GluA2-lacking AMPARs, occurred exclusively at synapses. The subunit composition and subcellular distribution of AMPARs and NMDARs are therefore distinctly regulated during homeostatic synaptic plasticity. Thus, because subunit composition dictates key channel properties, such as agonist affinity, gating kinetics, and calcium permeability, the homeostatic synaptic process transcends the simple modulation of synaptic strength by also regulating the signaling and integrative properties of central synapses.

Introduction

Hebbian forms of synaptic plasticity, i.e., long-term potentiation (LTP) and long-term depression (LTD), exhibit features that are consistent with a synaptic encoding of information and, as such, have come to dominate our understanding of how memories are stored in the brain (Kessels and Malinow, 2009). However, neural network models that implement solely Hebbian plasticity are inherently unstable due to the positive-feedback nature of LTP and LTD (Turrigiano, 2008; Lee et al., 2013). The discovery of homeostatic plasticity has been received with great interest in part because it provides a biologically plausible means to stabilize perpetually active and plastic neural networks (Turrigiano, 2008; Lazar et al., 2009; Lee et al., 2013). Homeostatic synaptic plasticity (HSP) enables neurons to adapt to sustained alterations in overall cellular activity by bidirectionally regulating the strength of excitatory and inhibitory synaptic transmission. For example, neurons respond to prolonged inactivity by a cell-wide enhancement of excitatory synaptic strength, and adapt to sustained hyperactivity by a global synaptic depression of excitatory synapses (Turrigiano et al., 1998).

Here, we show that prolonged network inactivity in organotypic hippocampal slices leads to a cell-wide surface delivery of calcium-permeable GluA2-lacking AMPARs that populate both synaptic and extrasynaptic sites. Synaptic NMDARs, but not their extrasynaptic counterparts, undergo a switch from predominantly GluN2B-containing to GluN2A-containing NMDARs in response to prolonged inactivity. These results, therefore, expand the known repertoire of the cellular processes involved in the homeostatic regulation of excitability of CA1 pyramidal neurons. The synaptic homeostatic response is thus not merely limited to the regulation of synaptic strength as a means to control excitability, but encompasses broader alterations that fundamentally influence key features of excitatory synaptic transmission.

For AMPAR current–voltage (I–V) curves, 0.1 mm spermine (Tocris Bioscience) was included in the internal solution. To calculate a rectification index for AMPAR I–V relationships, the slope was calculated for both the inward (−70 to 0 mV) and outward (0 to +40 mV) portions of the curve, and the ratio of the outward slope over the inward slope was computed (Béïque et al., 2011; Granger et al., 2013). The amplitudes of AMPA and NMDA currents for AMPA/NMDA ratios were estimated using the EPSC recorded at +40 mV, based on their respective time courses, as previously described (Béïque et al., 2006). For decay analysis of NMDAR-mediated EPSCs [both evoked EPSCs (eEPSCs) at +40 mV and uncaging EPSCs at −60 mV], a biexponential fit was used to calculate a weighted τ value (τw; Vicini et al., 1998). To ensure that all evoked currents were monosynaptic, extreme care has been taken to minimize polysynaptic activity. A glass-patch electrode was used to electrically stimulate glutamate release from axons and was positioned close to the proximal apical dendritic arbor of the recorded neurons. Stimulation intensity was kept low, eliciting eEPSCs of small amplitude (<100 pA, typically ∼50 pA). In some cases, 10–30 nm TTX was included in the Ringer's solution to dampen polysynaptic activity.

Peak-scaled nonstationary noise analysis of AMPAR-miniature EPSCs.

For estimates of mean AMPAR channel conductance (γ) and the number of channels exposed to glutamate (N), peak scaled noise analysis of AMPAR-miniature EPSCs (mEPSCs) was performed using Mini Analysis software (Synaptosoft). All recordings with <50 events were discarded from the analysis. An average mEPSC waveform from each recording was scaled to the peak of each mEPSC in the recording, and the variance of current fluctuations around the mean for each point in time was calculated. The average current variance relationship was then binned into 30 time points (independent of the amplitude of the average mEPSC), and the data were fit with the following parabolic equation:
where σ2 = variance, I = mean current, i = single-channel current, N = number of open channels at peak current, and b = background variance. From this equation, γ was calculated by dividing i by the driving force (−80 mV). Recordings were discarded if the parabolic fits of the current variance plots had R2 < 0.5. Since R2 values of the parabolic fits were generally >0.75, our estimate of N (i.e., number of channels) was not affected by a skewed variance versus mean relationship (Traynelis et al., 1993; Hartveit and Veruki, 2007).

Two-photon imaging and uncaging.

Simultaneous two-photon (2P) imaging and glutamate uncaging was performed using two Ti:Sapphire pulsed lasers (MaiTai-DeepSee; Spectra Physics) coupled to an Olympus MPE-1000 galvanometer scanning system. Before uncaging experiments, lasers were aligned to one another using fluorescent beads. One Ti:Sapphire laser was tuned to 810 nm to visualize morphology (Alexa Fluor 594), and the second laser was tuned to 720 nm for MNI-glutamate (MNI-Glu) uncaging. Synchronization of electrophysiological and optical equipment was accomplished using a Master-8 pulse generator (A.M.P.I.).

Glutamate uncaging experiments were performed with 2.5 mm MNI-glutamate trifluoroacetate (Femtonics) and tetrodotoxin supplemented to the Ringer's solution, while 0.03 mm Alexa Fluor 594 hydrazide (Na-salt; Invitrogen) was included in the internal recording solution. Whole-cell electrophysiological recordings were performed as described above. Neurons were allowed to fill with the dye for a minimum of 10 min before the onset of uncaging experiments. All two-photon uncaging EPSCs were generated from proximal secondary and tertiary apical dendrites to minimize issues of space clamp. The intensity of each laser was independently controlled using two independent acousto-optic modulators. The intensity of the uncaging laser was tuned to generate a 10–20 pA AMPAR-mediated 2P-EPSC at a holding potential of −70 mV for AMPAR–I–V curves. For NMDAR uncaging experiments, laser intensity was set to generate a NMDAR-mediated 2P-EPSC <25 pA when recorded in low-magnesium Ringer's solution (0.1 mm Mg2+, 3 mm Ca2+) at −60 mV in the presence of 0.01 mm NBQX (Tocris Bioscience) and 0.01 mm glycine. Because no particular care was taken to assure constant uncaging laser power between experiments in different neurons or slices (by normalizing for uneven light scattering at different tissue depth), we have not directly compared absolute amplitudes of 2P-EPSCs between experiments. Rather, we have compared metrics that are largely independent of laser power (i.e., rectification properties and decay kinetics: see Results). Uncaging laser power was, however, kept constant when uncaging was performed on neighboring spines and shaft regions of the same dendritic segment.

Image analysis.

For spine density and spine volume measurements, two-photon image stacks of proximal apical dendrites were obtained after a minimum of 30 min of dye filling following whole-cell access. Image stacks were gathered in optical sections of 0.5–0.7 μm, with an X–Y resolution between 0.05 and 0.1 μm/pixel. Spine density was calculated after manually sectioning apical dendritic reconstructions into 10 μm segments. Spine volume measurements were calculated using an intensity-based method, as previously described (Matsuzaki et al., 2001; Béïque et al., 2006). In cases where spine diameters (i.e., FWHM) are shown (see Figs. 7, 8), the intensity-based method of determining spine volume was not applicable due to limitations in the images gathered (i.e., images of spines from uncaging experiments were not gathered for volume analysis, which necessitates a high-resolution image containing many large and resolvable spines for calibrating the intensity-based methods). All measurements for spine volume and spine density were generated from unprocessed images.

Analysis of dendritic complexity was achieved using Neuron Studio analysis software (Computational Neurobiology and Imaging Center, Mount Sinai School of Medicine, New York, NY). Dendritic arbors of CA1 pyramidal neurons were modeled in Neuron Studio software, and dendritic complexity measurements were extracted. The dendritic complexity metric reported is an underestimate of the total dendritic complexity, as only apical regions were included in the analysis. Complexity of Alexa Fluor 594-filled CA1 pyramidal neurons from control- and TTX-treated slices [postnatal day 7 (P7) to P8 and 9–10 DIV] were compared with age-matched neurons from acute slices (P16–P18).

Equal concentrations of internal and surface proteins were loaded on SDS-PAGE, and Western blot was performed with the following antibodies: anti-GluN1 (1:3000, mouse monoclonal) and anti-glycine receptor (GlyR; 1:1000, mouse monoclonal) from Synaptic Systems; anti-GluN2A (1:1500, rabbit polyclonal), anti-GluN2B (1:1500, rabbit polyclonal), anti-GluA1 (1:1000 rabbit monoclonal) from Millipore; anti-GluA2 (1:2000, rabbit polyclonal) from Pierce Antibodies; and anti-β-actin (1:6000, mouse monoclonal) from Genscript. The chemiluminescent intensities were recorded using an Odyssey Fc Imaging System (LI-COR). Quantitative analyses were performed by determining the intensity of each band with Image Studio software (LI-COR).

Increased surface expression of GluA1 and the emergence of inwardly rectifying AMPARs at SC synapses following prolonged TTX treatment. A, Representative Western blots and quantification for the change in AMPA receptor subunit expression, plotted as a TTX/CTL ratio of band intensity, in hippocampal lysates from control and TTX-treated slices. All bands were normalized to β-actin before calculating the TTX/CTL ratio. B, Representative Western blots of biotinylated (surface) and nonbiotinylated (internal) fractions from control and TTX-treated hippocampal slices. Relative surface expression of AMPA and GlyR subunits from control and TTX-treated slices, plotted as a TTX/CTL ratio of band intensity. C, I–V relationship of evoked AMPAR-EPSCs. Left, Current traces at different holding potentials (−70 to +40 mV; with 100 μm intracellular spermine). Middle, Corresponding I–V curves from individual control and TTX-treated neurons. Right, Average I–V relationship of evoked AMPAR-EPSCs from control and TTX-treated neurons. D, Rectification indices for control and TTX-treated neurons in B, computed as the ratio of the slope (m) of the outward portion of the I–V curve over that of the inward portion (p < 0.01, unpaired Student's t test).

Synaptic incorporation of GluA2-lacking AMPARs in CA1 pyramidal neurons following prolonged TTX treatment. A, Left, Representative traces and event amplitude scatter plots of evoked AMPAR-EPSCs before and after NASPM administration (20 μm). Right, Normalized average amplitude of evoked AMPAR-EPSCs. B, Current traces and event amplitude scatter plots of spontaneous AMPAR-EPSCs (i.e., no TTX during recording; AMPAR-sEPSC) before (baseline) and 15–20 min after onset of NASPM (20 μm) administration. C, Average AMPAR-sEPSC amplitudes before (baseline) and 15–20 min after NASPM administration. D, Current traces and event amplitude scatter plots of AMPAR-mEPSCs (i.e., recorded in TTX) before and 15–20 min after onset of NASPM administration. E, Average AMPAR-mEPSC amplitudes before (baseline) and 15–20 min after NASPM administration.

Previous studies have demonstrated that synaptic strengthening during LTP is mediated by an increase in synaptic AMPAR number and is accompanied by robust dendritic spine enlargement (Matsuzaki et al., 2004; Harvey and Svoboda, 2007). Remarkably, we found that the synaptic strengthening during HSP was not accompanied by changes in the number of AMPARs at synapses (Fig. 2B), nor in the volume of dendritic spines (Fig. 2E). Rather, our biochemical, biophysical, and pharmacological data strongly suggest that the postsynaptic manifestation of HSP is expressed in part through the direct replacement of synaptic GluA2-containing AMPARs with higher-conductance GluA2-lacking AMPARs.

Homeostatic switch in synaptic NMDAR subunit composition

The dynamic nature of NMDAR trafficking and targeting behavior at rest, during postnatal development, and during Hebbian plasticity has gained considerable appreciation over the past 2 decades (Lau and Zukin, 2007). In part because HSP has overwhelmingly been studied in dissociated neuronal cultures, a preparation that does not lend itself with ease to the study of NMDAR function, the homeostatic regulation of NMDARs has been far less extensively studied than that of AMPARs (Pérez-Otaño and Ehlers, 2005). To determine whether alterations in NMDAR function accompanied the homeostatic enhancement in AMPAR function outlined above, we evoked EPSCs while holding neurons at −70 and +40 mV to compute the ratio of AMPAR and NMDAR contributions to SC synapse function (see Materials and Methods). We found that the ratio of AMPA to NMDA receptor components of eEPSCs was not altered by prolonged inactivity (CTL: 0.87 ± 0.13, n = 13 cells; TTX: 0.87 ± 0.12, n = 12 cells; p = 0.98; Fig. 5A), consistent with previous findings in both neuronal cultures and organotypic slices younger than those used here (Watt et al., 2000; Arendt et al., 2013). Since AMPAR function was significantly enhanced during HSP in our experimental conditions (Fig. 1B), this finding suggests a concomitant upregulation of both synaptic NMDA and AMPAR function during HSP. In line with this notion, Western blot analysis of hippocampal slice lysates (Fig. 5B) and surface biotinylation experiments (Fig. 5C) revealed an increase in the expression and surface delivery of all three major NMDAR subunits found in the hippocampus in TTX-treated slices (TTX/CTL ratio for hippocampal lysates: GluN1, 1.43 ± 0.09, n = 4; GluN2A, 1.52 ± 0.16, n = 6; GluN2B, 1.85 ± 0.13, n = 3; Fig. 5B; TTX/CTL ratio for biotinylated samples: GluN1, 1.31 ± 0.10, n = 10; GluN2A, 1.86 ± 0.35, n = 8; GluN2B, 1.69 ± 0.24, n = 15; Fig. 5C).

Homeostatic upregulation of surface NMDARs in CA1 pyramidal neurons in response to prolonged TTX treatment. A, AMPA/NMDA ratio of evoked EPSCs (see Materials and Methods). B, Representative Western blots and quantification of changes in NMDAR subunit expression, plotted as a TTX/CTL ratio of band intensity, in hippocampal lysates of control and TTX-treated slices. All bands were normalized to β-actin before calculating the TTX/CTL ratio. C, Representative Western blots of biotinylated (surface) and nonbiotinylated (internal) fractions from control and TTX-treated slices. Relative surface expression of NMDA receptor subunits between control and TTX-treated slices plotted as a TTX/CTL ratio of band intensity. D, Change in holding current induced by bath administration of 50 μmdl-APV while holding the neurons at +40 mV (p < 0.05, unpaired Student's t test). These experiments were performed with NBQX, picrotoxin, and TTX in the Ringer's solution. E, Amplitude of the inward current induced by bath administration of NMDA (5 μm; Vm = −60 mV in 0.1 mm Mg2+). All NMDA bath administration experiments were performed with NBQX, picrotoxin, and TTX in the Ringer's solution. F, 2P images of filled CA1 pyramidal neurons were reconstructed using Neuron Studio software (see Materials and Methods). Dendritic length (in micrometers) is plotted for CA1 pyramidal neurons from TTX-treated or control organotypic slices (P7 and 9–10 DIV) and from age-matched neurons from acute slices (P16–P17 animals; n = 10, 12, and 9 neurons for control, TTX-treated, and acute slices, respectively).

To further establish whether NMDAR function is homeostatically regulated in CA1 pyramidal neurons, we gathered two complementary electrophysiological readouts of NMDAR function. First, we reasoned that an upregulation of surface NMDARs could be revealed by examining the degree of tonic activation of these receptors by ambient levels of extracellular glutamate (Sah et al., 1989). To this end, we monitored changes in whole-cell current of CA1 pyramidal neurons induced by bath administration of the NMDAR antagonist dl-APV (50 μm; see Materials and Methods). NMDAR blockade in control neurons induced a small but highly reproducible change in holding current (15.48 ± 10.86 pA, n = 5 cells), thus revealing the presence of an ambient glutamate tone in organotypic hippocampal slices (Fig. 5D). Interestingly, the magnitude of this tonic current was more than three times greater in TTX-treated slices (56.15 ± 9.51 pA, n = 7 cells) compared with that seen in controls. In principle, this difference could reflect an upregulation of surface NMDARs, an alteration in the regulation of ambient extracellular glutamate concentration, or a combination of both. To directly measure NMDAR function, we next monitored the whole-cell response to bath administration of NMDA (5 μm for 3 min) and found that NMDA induced significantly larger whole-cell currents in TTX-treated neurons compared with control (CTL: 128.69 ± 15.44 pA, n = 16 cells; TTX: 198.98 ± 21.42 pA, n = 16 cells; p < 0.05; Fig. 5E). This enhancement was likely not due to an overall greater membrane surface area in TTX-treated neurons, since the dendritic arborization between control and TTX-treated neurons was not different (CTL: 732.36 ± 86.43 μm, n = 10 cells; TTX: 787.48 ± 48.56 μm, n = 12 cells; p = 0.56; Fig. 5F). These functional and morphological measurements aligned well with our biochemical data (Fig. 5B,C), and together they demonstrate that prolonged inactivity induced a robust upregulation of surface NMDAR expression in CA1 pyramidal neurons.

During Hebbian LTP, synaptic NMDARs undergo a rapid switch in subunit composition, from predominantly NR2B-containing toward NR2A-containing NMDARs (Bellone and Nicoll, 2007). We therefore next wondered about the degree of mechanistic commonality between Hebbian and homeostatic synaptic strengthening and asked whether the subunit composition of synaptic NMDARs is likewise regulated during homeostatic synaptic plasticity. To this end, we probed the subunit composition of synaptic NMDARs by first analyzing the kinetics of pharmacologically isolated NMDAR-eEPSCs from SC synapses and found that TTX-treated neurons exhibited NMDAR-eEPSCs with faster decay kinetics compared with control (τw: CTL, 366.03 ± 19.72 ms, n = 15 cells; TTX, 315.44 ± 15.16 ms, n = 18 cells; p < 0.05; Fig. 6A). Based on the well characterized subunit dependence of NMDAR kinetics (Vicini et al., 1998), these results suggest that prolonged inactivity led to synaptic enrichment of GluN2A-containing NMDARs. We further tested this possibility pharmacologically by measuring the sensitivity of NMDAR-eEPSCs to the GluN2B-containing NMDAR antagonist ifenprodil (3 μm) and found that NMDAR-eEPSCs recorded from TTX-treated neurons were significantly less sensitive to ifenprodil than interleaved controls (ifenprodil inhibition: CTL, 56.67 ± 4.80%, n = 12 cells; TTX, 37.95 ± 3.65%, n = 16 cells; p < 0.01; Fig. 6B). Thus, despite a robust upregulation of all three major NMDAR subunits at the plasma membrane, we found that GluN2A-containing NMDARs are preferentially stabilized at synapses during HSP.

Subcellular distribution of AMPAR and NMDAR subtypes following network silencing

The trafficking, targeting, and stabilization of glutamate receptors at synapses occurs through a number of highly regulated intracellular and extracellular interactions (Shepherd and Huganir, 2007). An emerging model of synaptic AMPAR recruitment involves the trapping of freely diffusing extrasynaptic surface receptors as they enter the synaptic compartment (Opazo and Choquet, 2011), and an analogous diffusional trapping mechanism has also been described for NMDARs (Groc et al., 2006; Bard et al., 2010). Moreover, the functional enhancement of AMPAR transmission during LTP is highly dependent on this reserve pool of nonsynaptic receptors (Makino and Malinow, 2009; Granger et al., 2013). Although our electrophysiological data outlined above clearly demonstrate that the subunit composition of synaptic AMPARs (Figs. 3, 4) and NMDARs (Fig. 6) are altered during HSP, it is unclear whether these changes reflect synapse-specific regulation or rather diffuse, cell-wide, changes in surface glutamate receptor expression. To specifically address this issue, we took advantage of subunit-specific biophysical signatures of AMPAR and NMDAR subtypes in combination with the ability afforded by 2P-uncaging of MNI-Glu to activate glutamate receptors at defined subcellular compartments (Fig. 7A–C).

Differential subcellular targeting of glutamate receptor subtypes during HSP. A, Top, AMPARs containing the GluA2 subunit predominate at both synaptic and extrasynaptic regions of CA1 pyramidal neurons. Bottom, When network activity is silenced by prolonged TTX treatment, there is a homeostatic upregulation of GluA2-lacking AMPARs in both synaptic and extrasynaptic compartments of the neuronal membrane. B, Top, CA1 pyramidal neurons display a mixed population of NMDARs containing both GluN2A and GluN2B subunits. Bottom, When network activity is silenced by prolonged TTX treatment, there is an indiscriminate increase in surface NMDARs subunits; however, GluN2A-containing NMDARs are preferentially localized/stabilized at synapses.

Discussion

Here, using a combination of biochemical, biophysical, and pharmacological approaches, we found that prolonged TTX treatment altered the subunit composition of both synaptic AMPARs and NMDARs in CA1 pyramidal neurons from organotypic hippocampal slices. Notably, we show that prolonged inactivity induced a robust upregulation of the AMPAR subunit GluA1 that resulted in a widespread, cell-wide, surface expression of GluA2-lacking AMPARs. Remarkably, despite inducing a robust and generalized upregulation of the three major hippocampal NMDAR subunits, network silencing triggered a switch in the subunit composition of solely the synaptic population of NMDARs, leaving unaltered the composition of their extrasynaptic counterparts. Altogether, these findings highlight the notion that the homeostatic mechanisms used by neurons to adjust their excitability levels regulate synapse function in ways beyond solely modifying synaptic strength per se.

A number of previous studies have reported conflicting evidence regarding the subunit composition of AMPARs involved in homeostatic synaptic potentiation. A recent review (Lee, 2012a) attempted to reconcile these discrepancies by documenting differences in the pharmacological paradigms used to induce HSP. Specifically, it was highlighted that the selective regulation of GluA1 occurred after prolonged blockade of both network activity (i.e., TTX) and NMDARs (Ju et al., 2004; Sutton et al., 2006; Aoto et al., 2008), whereas both GluA1 and GluA2 expression were affected when neurons were treated with TTX alone (O'Brien et al., 1998; Gainey et al., 2009; Anggono et al., 2011). In contrast to this unifying picture, we provide here a number of complementary and converging lines of evidence indicating that TTX treatment alone led to a robust and selective upregulation of GluA1 expression and formation of GluA2-lacking AMPARs in CA1 pyramidal neurons in an organotypic slice preparation. The direct replacement of GluA2-containing AMPARs with higher-conductance GluA2-lacking AMPARs during homeostatic plasticity offers an effective means to enhance synaptic strength without the need to increase receptor number or to increase spine volume. This scenario is consistent with homeostatic plasticity occurring at single synapses (Béïque et al., 2011) and is in line with manifestations of homeostatic synaptic plasticity in vivo (He et al., 2012).

It is pertinent to compare and contrast the mechanistic underpinnings of Hebbian and homeostatic synaptic strengthening, including those involving subunit composition of glutamate receptors. While a transient insertion of GluA2-lacking AMPARs has been observed following LTP induction (Plant et al., 2006; Guire et al., 2008), the role of this particular subtype of AMPARs in LTP is controversial (Adesnik and Nicoll, 2007; Gray et al., 2007). Likewise, the implication of GluA2-lacking AMPARs in homeostatic synaptic strengthening is also debated, as outlined above. These divergences may reflect the presence of distinct synaptic plasticity mechanisms that are heavily dependent on subtleties in experimental conditions and paradigms. Nevertheless, the homeostatic switch in NMDAR subunit composition we report here is highly analogous to that previously shown to occur during Hebbian LTP (Bellone and Nicoll, 2007). Indeed, LTP was shown to be accompanied by a GluN2B-containing toward GluN2A-containing NMDAR subunit switch that exhibited a time course highly similar to that of the synaptic delivery of AMPARs. Although our results provide limited insights into the precise time course of the inactivity-induced subunit switches for both AMPARs and NMDARs, these homeostatic adaptive mechanisms might be occurring simultaneously. It is thus tempting to speculate that both Hebbian and homeostatic synaptic strengthening use common mechanisms involving the concerted upregulation of AMPARs and GluN2A-containing NMDARs. Future studies will be required to substantiate this possibility and further establish the extent of the molecular commonalities between Hebbian and homeostatic synaptic plasticity.

The homeostatic adjustments reported here for both AMPAR and NMDAR subunit composition likely influence Hebbian plasticity rules. Indeed, in vivo visual deprivation paradigms that lead to homeostatic upregulation of synapse function in visual cortex (Goel and Lee, 2007; Gao et al., 2010) impart a metaplastic influence that modifies the stimulus threshold for inducing LTP and LTD (Philpot et al., 2001, 2003), and spike-timing-dependent synaptic plasticity (Guo et al., 2012). These changes appear to be caused by an increased proportion of GluN2B-containing NMDARs at synapses, in an apparent contrast to what we report here. Whereas the various in vivo visual deprivation paradigms reduce thalamic synaptic input into visual cortex, it is unclear to what extent they reduce overall network excitability in the visual cortex. Thus, it is possible that the GluN2A enrichment we report here following prolonged TTX treatment represents a homeostatic response to prolonged neuronal silencing, whereas the GluN2B enrichment observed following visual deprivation reflects a homeostatic response to a reduction in presynaptic activity. In support of this idea, selective presynaptic silencing of individual synapses has recently been shown to cause postsynaptic GluN2B enrichment (Lee et al., 2010). Conversely, the presence of calcium-permeable GluA2-lacking AMPARs following prolonged inactivity may also convey metaplastic influences to synapses, either by lowering the threshold for Hebbian synaptic potentiation, or even by imparting anti-Hebbian features (Lamsa et al., 2007). Future studies are required to better understand the influence of glutamate receptor composition on synaptic plasticity rules.

AMPARs and NMDARs of different subunit composition are differentially localized to synaptic and extrasynaptic membrane compartments. For instance, AMPARs containing GluA2/GluA3 subunits are found almost exclusively at synapses, whereas GluA1/GluA2-AMPARs occupy both synaptic and extrasynaptic membrane regions (Béïque and Huganir, 2009; Lu et al., 2009). Moreover, GluN2A-containing NMDARs are believed to be preferentially stabilized at synapses over GluN2B-containing NMDARs (Groc et al., 2006). These subcellular distribution profiles are thought to arise through preferential interactions of specific AMPAR and NMDAR subunits, and/or auxiliary subunits, with PSD scaffolding proteins at synapses (Lau and Zukin, 2007; Shepherd and Huganir, 2007; Jackson and Nicoll, 2011). The differential subcellular distribution of AMPAR and NMDAR expression during HSP that we have described can be traced, at least in part, to the changes in subunit protein expression. Specifically, the selective upregulation of GluA1 protein expression (over GluA2) was accompanied by a widespread enhancement of surface GluA2-lacking AMPARs, evident at both dendritic spines and extrasynaptic membrane regions. Such a cell-wide upregulation of AMPARs offers an effective means to account for the remarkable multiplicativity of homeostatic synaptic strengthening triggered by a somatic homeostatic sensing mechanism (Lee et al., 2013). Interestingly, the TTX-induced increase in NMDAR protein expression (both total and surface expression) was not subunit selective, as we detected an upregulation of GluN1, GluN2A, and GluN2B. Despite this generalized increase in NMDAR surface expression, synapses were specifically enriched with GluN2A-containing NMDARs during HSP, likely reflecting the preferential synaptic stabilization of this subunit compared with GluN2B-containing NMDARs. Thus, whereas the synaptic incorporation of GluA2-lacking AMPARs likely results from the bulk loading of these receptors onto the plasma membrane, the selective synaptic stabilization of GluN2A-containing NMDARs during HSP emphasizes the competitive interactions of GluN2A subunits for synaptic anchoring/scaffolding proteins.

The functional importance of extrasynaptic receptors is increasingly being recognized. For instance, extrasynaptic AMPARs and NMDARs can be recruited to and/or exchanged with synaptic receptor populations in a dynamic and highly regulated manner. Recent studies have shown that extrasynaptic AMPARs can shape synaptic transmission (Heine et al., 2008) and are required for LTP (Makino and Malinow, 2009; Granger et al., 2013). Moreover, extrasynaptic NMDARs can powerfully influence synaptic integration (Chalifoux and Carter, 2011; Lee, 2012b) and differentially regulate neuronal survival and death signaling pathways (Hardingham and Bading, 2003). The homeostatic regulation of the number and subunit composition of extrasynaptic glutamate receptors described here will, in principle, influence all of the functions ascribed to this population of receptors, thus broadening the functional implications of the homeostatic process.

Both in vitro and in vivo manifestations of homeostatic synaptic plasticity have been documented using several experimental paradigms. Homeostatic synapse regulation operates continuously “online” to enable tuning of cellular excitability in the face of perpetual alterations in neuronal firing activity. We have demonstrated that, in addition to triggering robust synaptic strengthening, the homeostatic process also involves changes in the subunit composition and subcellular distribution of both AMPARs and NMDARs. Thus, the homeostatic adjustment of synapse function is not limited to the regulation of synaptic strength, but likely impacts synaptic properties such as temporal integration of synaptic input and calcium-dependent biochemical signaling. Future studies will be required to fully grasp the functional implications of these homeostatic regulations.

Footnotes

This research was funded by the Heart and Stroke Foundation Center for Stroke Recovery, the Canadian Institute of Health Research, the Natural Sciences and Engineering Research Council of Canada, and the Canadian Foundation for Innovation (to J.C.B.). We thank Nina Ahlskog for her valuable contribution in setting up the surface biotinylation assay; Riadh Haj-Dahmen for his assistance in the early phases of the project; and members of the Béïque and Bergeron laboratories for helpful discussions.